Dataset Information

Non-conventional Inhibitory CD4+Foxp3-PD-1hi T Cells as a Biomarker of Immune Checkpoint Blockade Activity.

ABSTRACT: A significant proportion of cancer patients do not respond to immune checkpoint blockade. To better understand the molecular mechanisms underlying these treatments, we explored the role of CD4+Foxp3- T cells expressing PD-1 (4PD1hi) and observed that 4PD1hi accumulate intratumorally as a function of tumor burden. Interestingly, CTLA-4 blockade promotes intratumoral and peripheral 4PD1hi increases in a dose-dependent manner, while combination with PD-1 blockade mitigates this effect and improves anti-tumor activity. We found that lack of effective 4PD1hi reduction after anti-PD-1 correlates with poor prognosis. Mechanistically, we provide evidence that mouse and human circulating and intra-tumor 4PD1hi inhibit T cell functions in a PD-1/PD-L1 dependent fashion and resemble follicular helper T cell (TFH)-like cells. Accordingly, anti-CTLA-4 activity is improved in TFH deficient mice.

SUBMITTER: Zappasodi R

PROVIDER: S-EPMC6648657 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Non-conventional Inhibitory CD4+Foxp3-PD-1hi T Cells as a Biomarker of Immune Checkpoint Blockade Activity.

Zappasodi Roberta R Budhu Sadna S Hellmann Matthew D MD Postow Michael A MA Senbabaoglu Yasin Y Manne Sasikanth S Gasmi Billel B Liu Cailian C Zhong Hong H Li Yanyun Y Huang Alexander C AC Hirschhorn-Cymerman Daniel D Panageas Katherine S KS Wherry E John EJ Merghoub Taha T Wolchok Jedd D JD

Cancer cell 20180601 6

A significant proportion of cancer patients do not respond to immune checkpoint blockade. To better understand the molecular mechanisms underlying these treatments, we explored the role of CD4+Foxp3- T cells expressing PD-1 (4PD1hi) and observed that 4PD1hi accumulate intratumorally as a function of tumor burden. Interestingly, CTLA-4 blockade promotes intratumoral and peripheral 4PD1hi increases in a dose-dependent manner, while combination ...[more]

PMID: 29894689

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Project description:BackgroundStratification of patients who could benefit from immune checkpoint inhibitor (ICI) therapy is of much importance. PD-1hiCD8+ T cells represent a newly identified and effective biomarker for ICI therapy response biomarker in lung cancer. Accurately quantifying these T cells using commonly available RNA sequencing (RNA-seq) data may extend their applications to more cancer types.MethodWe built a transcriptome signature of PD-1hiCD8+ T cells from bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data of tumor-infiltrating immune cells. The signature was validated by flow cytometry and in independent datasets. The clinical applications of the signature were explored in non-small-cell lung cancer, melanoma, gastric cancer, urothelial cancer, and a mouse model of breast cancer samples treated with ICI, and systematically evaluated across 21 cancer types in The Cancer Genome Atlas (TCGA). Its associations with other biomarkers were also determined.ResultsSignature scores could be used to identify the PD-1hiCD8+ T subset and were correlated with the fraction of PD-1hiCD8+ T cells in tumor tissue (Pearson correlation, R=0.76, p=0.0004). Furthermore, in the scRNA-seq dataset, we confirmed the capability of PD-1hiCD8+ T cells to secrete CXCL13, as well as their interactions with other immune cells. In 581 clinical samples and 204 mouse models treated with ICIs, high signature scores were associated with increased survival, and the signature achieved area under the receiver operating characteristic curve scores of 0.755 (ranging from 0.61 to 0.91) in predicting therapy response. In TCGA pan-cancer datasets, our signature scores were consistently correlated with therapy response (R=0.78, p<0.0001) and partially explained the diverse response rates among different cancer types. Finally, our signature generally outperformed other mRNA-based predictors and showed improved predictive performance when used in combination with tumor mutational burden (TMB). The signature score is available in the R package "PD1highCD8Tscore" (https://github.com/Liulab/PD1highCD8Tscore).ConclusionThrough estimating the fraction of the PD-1hiCD8+ T cell, our signature could predict response to ICI therapy across multiple cancers and could serve as a complementary biomarker to TMB.

Project description:ImportancePD-L1 (programmed cell death ligand 1) immunohistochemistry (IHC), tumor mutational burden (TMB), gene expression profiling (GEP), and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) assays have been used to assess pretreatment tumor tissue to predict response to anti-PD-1/PD-L1 therapies. However, the relative diagnostic performance of these modalities has yet to be established.ObjectiveTo compare studies that assessed the diagnostic accuracy of PD-L1 IHC, TMB, GEP, and mIHC/IF in predicting response to anti-PD-1/PD-L1 therapy.Evidence reviewA search of PubMed (from inception to June 2018) and 2013 to 2018 annual meeting abstracts from the American Association for Cancer Research, American Society of Clinical Oncology, European Society for Medical Oncology, and Society for Immunotherapy of Cancer was conducted to identify studies that examined the use of PD-L1 IHC, TMB, GEP, and mIHC/IF assays to determine objective response to anti-PD-1/PD-L1 therapy. For PD-L1 IHC, only clinical trials that resulted in US Food and Drug Administration approval of indications for anti-PD-1/PD-L1 were included. Studies combining more than 1 modality were also included. Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines were followed. Two reviewers independently extracted the clinical outcomes and test results for each individual study.Main outcomes and measuresSummary receiver operating characteristic (sROC) curves; their associated area under the curve (AUC); and pooled sensitivity, specificity, positive and negative predictive values (PPV, NPV), and positive and negative likelihood ratios (LR+ and LR-) for each assay modality.ResultsTumor specimens representing over 10 different solid tumor types in 8135 patients were assayed, and the results were correlated with anti-PD-1/PD-L1 response. When each modality was evaluated with sROC curves, mIHC/IF had a significantly higher AUC (0.79) compared with PD-L1 IHC (AUC, 0.65, P < .001), GEP (AUC, 0.65, P = .003), and TMB (AUC, 0.69, P = .049). When multiple different modalities were combined such as PD-L1 IHC and/or GEP + TMB, the AUC drew nearer to that of mIHC/IF (0.74). All modalities demonstrated comparable NPV and LR-, whereas mIHC/IF demonstrated higher PPV (0.63) and LR+ (2.86) than the other approaches.Conclusions and relevanceIn this meta-analysis, tumor mutational burden, PD-L1 IHC, and GEP demonstrated comparable AUCs in predicting response to anti-PD-1/PD-L1 treatment. Multiplex immunohistochemistry/IF and multimodality biomarker strategies appear to be associated with improved performance over PD-L1 IHC, TMB, or GEP alone. Further studies with mIHC/IF and composite approaches with a larger number of patients will be required to confirm these findings. Additional study is also required to determine the most predictive analyte combinations and to determine whether biomarker modality performance varies by tumor type.

Dataset Information

Non-conventional Inhibitory CD4+Foxp3-PD-1hi T Cells as a Biomarker of Immune Checkpoint Blockade Activity.

Publications

Non-conventional Inhibitory CD4<sup>+</sup>Foxp3<sup>-</sup>PD-1<sup>hi</sup> T Cells as a Biomarker of Immune Checkpoint Blockade Activity.

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